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Why shouldn't classes overlap when summarizing continuous data in a frequency or relative frequency distribution? Choose the correct answer below. A. Classes shouldn't overlap so that the distribution is not skewed in one direction. B. Classes shouldn't overlap so that the class width is as small as possible. C. Classes shouldn't overlap so there is no confusion as to which class an observation belongs. D. Classes shouldn't overlap so that they are open ended.

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  1. 3 May, 22:04
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    C. Classes shouldn't overlap so there is no confusion as to which class an observation belongs.

    Explanation:

    When summarizing data that is continuous in a frequency or relative frequency distribution, the classes should be accurately entered to avoid overlapping. This is because overlapping causes confusion between classes and observations. Consequently leading to wrong results from the data.
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